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COMPARATIVE ANALYSIS ON MACHINE LEARNING MODELS FOR PREDICTING KOSPI200 INDEX RETURNS

  • Gu, Bonsang (Department of Economics, Hankuk University of Foreign Studies) ;
  • Song, Joonhyuk (Department of Economics, Hankuk University of Foreign Studies)
  • Received : 2017.09.18
  • Accepted : 2017.10.08
  • Published : 2017.11.30

Abstract

In this paper, machine learning models employed in various fields are discussed and applied to KOSPI200 stock index return forecasting. The results of hyperparameter analysis of the machine learning models are also reported and practical methods for each model are presented. As a result of the analysis, Support Vector Machine and Artificial Neural Network showed a better performance than k-Nearest Neighbor and Random Forest.

Acknowledgement

Supported by : Hankuk University

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